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检索条件"丛书名=Computer engineering series"

共 367966 条记录，以下是51-60 订阅

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Short-Term Load Demand Forecasting Using Multinomial Naive Bayes with Support Vector Machine 16

Short-Term Load Demand Forecasting Using Multinomial Naive B...

引用

16th International Conference on computer and Automation engineering (ICCAE)

作者： Dansalan, Jan Franchezka Diaz, Jedidia Ostia, Conrado, Jr. Mapua Univ Dept Elect Elect & Comp Engn Manila Philippines

ISBN: (纸本)9798350370058;9798350370164

Predicting the necessary power to maintain a balanced supply and demand is crucial for the efficient operation of power-providing companies. This study employs a load forecasting model utilizing Multinomial Naive Bayes in conjunction with a Support Vector Machine. The objective is to investigate and evaluate the performance of these algorithms on a designated dataset, thereby advancing the knowledge base of load forecasting models. The study compares three approaches: Multinomial Naive Bayes, Support Vector Machine, and a hybrid approach combining both. Results indicate that the Support Vector Machine algorithm demonstrates remarkable accuracy, achieving an average Mean Absolute Percentage Error (MAPE) of 1.48%. Multinomial Naive Bayes also exhibit commendable precision with an average MAPE of 3.93%. Furthermore, the hybrid approach yields promising results, attaining an average MAPE of 1.95%. Statistical analysis proves a significant difference between the hybrid algorithm and the individual approaches.

关键词： Load forecasting Multinomial Naive Bayes Support Vector Machine Algorithm Performance

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Defect, Size, Maturity, and Quality Detection on Ladies' Finger, Bitter Gourd, and Cucumber using Image Processing and MobileNetV2 16

Defect, Size, Maturity, and Quality Detection on Ladies' Fin...

引用

16th International Conference on computer and Automation engineering (ICCAE)

作者： Valiente, Flordeliza L. Lozano, Mark Olsen B. Ricasio, Stephanie E. Valiente, Leonardo D., Jr. Mapua Univ Sch Elect Elect & Comp Engn 658 Muralla St Intramuros Manila Philippines

ISBN: (纸本)9798350370058;9798350370164

Image processing has been proven to be an effective technique for analysis in various fields, including agriculture. In agriculture, image processing is applied to crops or the quality of products by detection, classification, and grading. With that being said, applying a deep learning algorithm to image processing for defect, size, maturity, and quality detection on ladies' fingers, bitter gourds, and cucumbers can be difficult. An expert's advice and service may often be expensive and time-consuming. Image processing techniques and a deep learning algorithm will benefit farmers by classifying the defect, size, maturity, and quality of the ladies' finger, bitter gourd, and cucumber accurately and in realtime. This paper intends to focus on the detection of the defect, size, maturity, and quality of the ladies' finger, bitter gourd, and cucumber using Watershed Algorithm, Otsu Thresholding, RGB Masking, K-means Cluster Algorithm, and MobileNetV2. Moreover, this study detected the defect, size, maturity, and quality of the vegetables correctly, and the algorithm and techniques used were effective and accurate.

关键词： Vegetables Ladies' Finger Bitter Gourd Cucumber Deep Learning

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A Tight Convex Model of Optimal Gas Flow Problem in Local Networks: Distributed Gas and Power Scheduling Application

A Tight Convex Model of Optimal Gas Flow Problem in Local Ne...

引用

IEEE Canadian Conference on Electrical and computer engineering (CCECE)

作者： Alizadeh, Ali Kamwa, Innocent Cao, Bo Xu, Minghui Laval Univ Dept Elect Engn Quebec City PQ Canada Huawei Technol Canada Co Ltd Smart Grid Technol Lab Montreal PQ Canada

ISBN: (纸本)9798350371635;9798350371628

Integrated scheduling of gas and power in local networks using distributed algorithms can not only improve the cost of gas and power systems but also preserve their privacy. However, the nonconvexity of the gas flow problem (GFP) is an obstacle to this purpose. This paper proposes a tight convex hull for GFP in which the second-order conic programming (SOCP) technique is utilized to remove the nonconvexity and a push is developed to improve the tightness. Then, a distributed algorithm of integrated gas and power scheduling is developed using the proximal consensus alternative direction method of multipliers (PC-ADMM). The results and comparisons confirm the efficiency of the proposed model.

关键词： Gas Flow Problem Tight Second-Order Conic Relaxation Proximal Consensus Alternative Direction Method of Multipliers Convexity

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A Survey on the Integration and Optimization of Large Language Models in Edge Computing Environments 16

A Survey on the Integration and Optimization of Large Langua...

引用

16th International Conference on computer and Automation engineering (ICCAE)

作者： Bhardwaj, Sarthak Singh, Pardeep Pandit, Mohammad Khalid Natl Inst Technol Dept Comp Sci Hamirpur India

ISBN: (纸本)9798350370058;9798350370164

In this survey, we delve into the integration and optimization of Large Language Models (LLMs) within edge computing environments, marking a significant shift in the artificial intelligence (AI) landscape. The paper investigates the development and application of LLMs in conjunction with edge computing, highlighting the advantages of localized data processing such as reduced latency, enhanced privacy, and improved efficiency. Key challenges discussed include the deployment of LLMs on resource-limited edge devices, focusing on computational demands, energy efficiency, and model scalability. This comprehensive analysis underscores the transformative potential and future implications of combining LLMs with edge computing, paving the way for advanced AI applications across various sectors.

关键词： Large Language Models Edge Computing Model Optimization Real-time Data Processing Edge AI Model Adaptability Pruning Model Quantization

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Sarid: Arabic Storyteller Using a Fine-Tuned LLM and Text-to-Image Generation 16

Sarid: Arabic Storyteller Using a Fine-Tuned LLM and Text-to...

引用

16th International Conference on computer and Automation engineering (ICCAE)

作者： Alabdulrahman, Maria Khayyat, Renad Almowallad, Kawthar Alharz, Zahra Prince Mohammad Bin Fahd Univ Al Khobar Saudi Arabia King Abdulaziz Univ Jeddah Saudi Arabia Imam Abdulrahman Bin Faisal Univ Al Khobar Saudi Arabia

ISBN: (纸本)9798350370058;9798350370164

We propose a novel approach to Arabic story generation by fine-tuning a pre-trained Large Language Model (LLM). Our pipeline includes two stages: text generation and image generation. By fine-tuning the davinci-003 LLM on a dataset of 527 Arabic stories, we tailor the generated stories based on user preferences. For image generation, we utilize the Midjourney model. The results demonstrate the efficacy of fine-tuning a pre-trained image generation model on a limited dataset, as measured by the ROUGE score. Sarid's contributions include addressing the lack of Arabic story generation models, providing a comprehensive dataset of Arabic stories, and integrating text and image generation for a cohesive story generation pipeline.

关键词： Artificial Intelligence Fine-tuning Generative Models Image Generation Text Generation

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Probabilistic Multi-Objective Optimal Power Flow: A Grey Wolf Optimizer Approach Considering Load and Wind Turbine Uncertainties

Probabilistic Multi-Objective Optimal Power Flow: A Grey Wol...

引用

IEEE Canadian Conference on Electrical and computer engineering (CCECE)

作者： Amini, Shiva Kamwa, Innocent Nahvi, Shabbo Golpira, Hemin Laval Univ Dept Elect & Comp Sci Engn Quebec City PQ Canada Univ Kurdistan Dept Elect & Comp Engn Sanandaj Iran Univ Kurdistan Dept Elect & Comp Engn Power Syst Modeling & Simulat Lab Sanandaj Iran

ISBN: (纸本)9798350371635;9798350371628

This article presents a novel approach to tackle the challenge of Probabilistic Multi-Objective Optimal Power Flow (PMOOPF) by utilizing the Grey Wolf Optimizer (GWO). The methodology incorporates uncertainties related to both load and wind turbine generation, modeling load uncertainty with a normal distribution and wind speed uncertainty with a Weibull distribution and employs Monte Carlo Simulation (MCS) to establish the probability distribution function (PDF) for both the load and power generated by the hybrid sources. The PMOOPF problem aims to concurrently minimize thermal generation costs, real power losses, and maximize voltage stability. The proposed approach is tested on the IEEE 26-bus system, and the outcomes are compared with the Gravitational Search Algorithm (GSA). The contribution of this paper lies in effectively addressing uncertainties in load and wind turbine generation, incorporating diverse PMOOPF objectives, and employing the GWO optimization technique. The simulation results demonstrate the method's efficacy and efficiency in achieving economic and technical benefits.

关键词： Probabilistic Multi-Objective Optimal Power Flow uncertainties wind turbine generation

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Hierarchical Tracking Control for a Composite Mobile Robot Considering System Uncertainties 16

Hierarchical Tracking Control for a Composite Mobile Robot C...

引用

16th International Conference on computer and Automation engineering (ICCAE)

作者： Yan, Yiming Guo, Fusen Mo, Huadong Huang, Xueting Southeast Univ Sch Mech Engn Nanjing Peoples R China Swinburne Univ Technol Sch Sci Comp & Engn Technol Melbourne Vic Australia Univ New South Wales Sch Engn & Informat Technol Canberra ACT Australia Guangzhou Coll Commerce Fac Art design Guangzhou Peoples R China

ISBN: (纸本)9798350370058;9798350370164

Composite mobile robots (CMRs) have gained extensive application in the industrial sector due to their integrated loading and operational capabilities. The trajectory tracking control module, being a vital constituent, directly influences the degree of stability in robot operations. However, current tracking control methods exhibit suboptimal performance when encountering system uncertainties arising from both the environment and inherent system factors. This paper presents a novel hierarchical control strategy tailored for the hierarchical model of composite mobile robot chassis. This strategy effectively combines velocity control and torque control, resulting in satisfactory trajectory tracking control. Firstly, a hierarchical kinematic and dynamic model is constructed to account for varying payload and environmental uncertainties. Subsequently, a pose-velocity-torque hierarchical controller is formulated to regulate chassis speed by manipulating torque input, thereby achieving pose regulation and trajectory tracking. Finally, the control algorithm is implemented using MATLAB and adapted to industrial computers for the development and validation of the controller's effectiveness. Comparative experiments are conducted against existing methods, demonstrating the superiority of the proposed controller.

关键词： composite mobile robots pose-velocity-torque hierarchical controller trajectory tracking system uncertainties

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Investigation of The Latest Malware Detection Engines and Lightweight Byte n-gram Methods with Real Custom Malware 16

Investigation of The Latest Malware Detection Engines and Li...

引用

16th International Conference on computer and Automation engineering (ICCAE)

作者： Uda, Ryuya Araki, Shinnosuke Tokyo Univ Technol Sch Comp Sci 1404-1 Katakuramachi Hachioji Tokyo 1920982 Japan

ISBN: (纸本)9798350370058;9798350370164

Almost all malware detection systems are black boxes to the general users. The simple pattern matching method is the fastest, but it becomes useless if some bytes in a malware file are changed. Therefore, in this paper, we investigated what kind of customization influences the detection rate of the latest malware detection engines. In addition, we also investigated whether byte n-gram and information gain malware detection methods are effective in detecting the custom malware files. These methods have been proposed and improved by some researchers, but the computational cost of information gain was too high to be used in the real world. Therefore, we proposed a lightweight method of the methods and evaluated the custom files. With this method, we could find only 9 to 13 out of 32 to 33 malware files in 5-hold cross-validation, but it was 15 to 21 in original files. This means that the byte n-gram method can work if it detects a malware file once. On the other hand, almost all of the malware files were not detected by almost all of the latest engines. We conclude that the byte n-gram methods are still effective when malware changes itself, and lightweight methods with better detection rates are needed.

关键词： malware detection byte n-grams information security

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computer Vision Fire Hydrant Obstruction Detection System

Computer Vision Fire Hydrant Obstruction Detection System

引用

IEEE Canadian Conference on Electrical and computer engineering (CCECE)

作者： Ibrahim, Nader Dick, Kevin Green, James R. Carleton Univ Dept Syst & Comp Engn Ottawa ON Canada

ISBN: (纸本)9798350371635;9798350371628

Well-maintained and accessible fire hydrant infrastructure can reduce response times and minimize fire damage. Hydrant access and visibility can be impeded by transient obstructions, such as illegally parked vehicles, or by incremental obstructions, such as snow coverage or encroachment of vegetation. We here develop a computer vision system to automatically survey all hydrants within a city to determine whether they are accessible, partially obstructed, or fully obstructed. The system is developed and validated using Google Streetview images from three distinct urban environments. The dataset is augmented with winter weather and synthetic obstructions, including snowbanks. A YOLOv8 model is fine-tuned to detect fire hydrants. Partially obstructed hydrants are then detected using a bounding box aspect ratio threshold. Evaluation on a test city results in an mAP of 97.1%, indicating strong hydrant detection performance, even in challenging scenarios such as partially snow-covered hydrants. Partially blocked hydrants are classified with precision and recall of 92%. Results are displayed on a geographic information system dashboard for maintenance and bylaw personnel to ensure continuous access to this critical firefighting infrastructure.

关键词： Fire Hydrant computer Vision (CV) Artificial intelligence (AI) Critical Infrastructure You Only Look Once v8 (YOLOv8) Generative AI

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Utilizing Multiple UAVs for Covert Aerial Monitoring of a Mobile Target through Decentralized Priority-Based Trajectory Planning 16

Utilizing Multiple UAVs for Covert Aerial Monitoring of a Mo...

引用

16th International Conference on computer and Automation engineering (ICCAE)

作者： Almuzaini, Talal Univ New South Wales Sch Elect Engn & Telecommun Sydney Australia Islamic Univ Madinah Sch Elect Engn Madinah Saudi Arabia

ISBN: (纸本)9798350370058;9798350370164

Autonomous aerial robots or unmanned aerial vehicles (UAVs) are widely used in target surveillance and monitoring for various purposes due to their affordability, mobility, and flexibility. This study presents a decentralized priority-based approach for planning the flight paths of multiple UAVs engaged in covert aerial monitoring of a mobile target. This method aims to address the challenge of coordinating UAVs' trajectories to minimize the risk of collisions while ensuring a high level of camouflage. The decentralized approach involves each UAV autonomously planning its trajectory based on local data and shared information with other UAVs. The generated flight paths of each UAV are designed to remain visually concealed from the target and are energy-efficient. Furthermore, the approach incorporates the prioritization concept, where UAVs with lower disguising performance receive higher priority in collision avoidance situations that might occur during the movement along the generated paths. This prioritization reduces the risk of the target being aware of the UAVs. The proposed method is evaluated through comprehensive computer simulations conducted in MATLAB, demonstrating its effectiveness in preventing UAV collisions while sustaining a high level of camouflage.

关键词： Autonomous aerial robots trajectory planning collision avoidance prioritized planning covert aerial monitoring visual camouflage

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